The value evolution graph and its use in memory reference analysis

Parallel Architectures and Compilation Techniques - Conference Proceedings, PACT

Volumn , Issue , 2004, Pages 243-254

  Rus, Silvius ^a   Zhang, Dongmin ^a   Rauchwerger, Lawrence ^a  

^a TEXAS A AND M UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA FLOW; GRAPH PATHS; VALUE EVALUATION GRAPH (VEG);

ALGORITHMS; ARRAYS; DATA TRANSFER; GRAPH THEORY; PROBLEM SOLVING; PROGRAM COMPILERS;

DATA STRUCTURES;

EID: 10444238441     PISSN: 1089795X     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. Z. Ammarguellat and W. L. Harrison, III. Automatic recognition of induction variables and recurrence relations by abstract interpretation. In ACM SIGPLAN '90 Conf. on Prog. Language Design and Implementation, 1990.
2. R. A. Ballance, A. B. Maccabe, and K. J. Ottenstein. The Program Dependence Web: A representation supporting control-, data-, and demand-driven interpretation of imperative languages. In ACM SIGPLAN '90 Conf. on Prog. Language Design and Implementation, pp. 257-271, White Plains, N.Y., June 1990.
3. W. Blume and R. Eigenmann. The Range Test: A Dependence Test for Symbolic, Non-linear Expressions. Proc. of Supercomputing '94, Nov. 1994.
4. W. Blume and R. Eigenmann. Symbolic Range Propagation. TR 1381, Univ. of Illinois at Urbana-Champaign, Cntr for Supercomputing Res & Dev, Oct 1994.
5. D. Callahan. Recognizing and parallelizing bounded recurrences. In 7997 Workshop on Languages and Compilers for Parallel Computing, number 589 in LNCS, pp. 169-185, Springer Verlag, Berlin.
6. S.-C. Chen and D. J. Kuck. Time and parallel processor bounds for linear recurrence systems. IEEE Trans. on Computers, 24(7):701-717, 1975.
7. A. L. Fisher and A. M. Ghuloum. . Parallelizing complex scans and reductions. In Proc. of the ACM SIGPLAN 1994 Conf. on Prog. Language Design and Implementation, pp. 135-146. ACM Press, 1994.
8. M. P. Gerlek, E. Stolz, and M. Wolfe. Beyond induction variables: Detecting and classifying sequences using a demand-driven SSA form. ACM Trans. on Prog. Languages and Systems, 17(1):85-122, 1995.
9. A. M. Ghuloum and A. L. Fisher. Flattening and parallelizing irregular, recurrent loop nests. In Proc. of the 5-th ACM SIGPLAN Symp. on Principles and Practice of Parallel Prog., pp. 58-67. ACM Press, 1995.
10. J. Gu, Z. Li, and G. Lee. Symbolic array dataflow analysis for array privatization and program parallelization. In Conf. on Supercomputing, 1995.
11. M. Gupta, S. Mukhopadhyay, and N. Sinha. Automatic parallelization of recursive procedures. Int. J. of Parallel Prog., 28(6):537-562, 2000.
12. R. Gupta. Optimizing array bound checks using flow analysis. ACM Letters on Prog. Lang. and Systems, 2(1-4), 1993.
13. M. R. Haghighat and C. D. Polychronopoulos. Symbolic analysis for parallelizing compilers. ACM Trans. on Prog. Lang, and Systems, 18(4):477-518, 1996.
14. M. Hall, J. Anderson, S. Amarasinghe, B. Murphy, S.-W. Liao, E. Bugnion, and M. Lam. Maximizing Multiprocessor Performance with the SUIF Compiler. IEEE Computer, 29(12):84-89, Dec. 1996.
15. J. Hoeflinger. Interprocedural Parallelization Using Memory Classification Analysis. PhD thesis, University of Illinois, Urbana-Champaign, Aug., 1998.
16. J. JàJà. An Introduction Parallel Algorithms. Addison-Wesley, Reading, MA, 1992.
17. S.-W. Liao, A. Diwan, R. P. B. Jr., A. M. Ghuloum, and M. S. Lam. SUIF explorer: An interactive and interprocedural parallelizer. In Principlesd Pract. of Parallel Prog., 1999.
18. Y. Lin and D. Padua. Analysis of irregular single-indexed array accesses and its application in compiler optimizations. In Int. Conf. on Compiler Construction, 2000.
19. Y. Lin and D. A. Padua. On the automatic parallelization of sparse and irregular fortran programs. In 7998 Workshop on Languages and Compilers for Parallel Computing.
20. W. Pottenger and R. Eigenmann. Parallelization in the presence of generalized induction and reduction variables. TR 1396, Univ. of Illinois at Urbana Champaign, Cntr. for Supercomputing Res. & Dev., Jan. 1995.
21. W. Pugh. The Omega test: A fast and practical integer programming algorithm for dependence analysis. In Supercomputing '97, pp. 4-13, Albuquerque, N.M., Nov. 1991.
22. L. Rauchwerger and D. A. Padua. The LRPD Test: Speculative Run-Time Parallelization of Loops with Privatization and Reduction Parallelization. IEEE Trans. on Parallel and Distributed Systems, 10(2), 1999.
23. L. Rauchwerger and D. A. Padua. Parallelizing WHILE Loops for Multiprocessor Systems. In Proc. of 9th Int. Parallel Processing Symp., April 1995.
24. J. R. Reif and H. R. Lewis. Symbolic evaluation and the global value graph. In 4th ACM Symp. on Principles of Prog. Languages, pp. 104-118, 1977.
25. S. Rus, J. Hoeflinger, and L. Rauchwerger. Hybrid analysis: static & dynamic memory reference analysis. Int. J. of Parallel Prog., 31(3):251-283, 2003.
26. M. Spezialetti and R. Gupta. Loop monotonic statements. IEEE Trans. on Software Engineering, 21(6), 1995.
27. R. Triolet, F. Irigoin, and P. Feautrier. Direct parallelization of Call statements. In ACM SIGPLAN '86 Symp. on Compiler Construction, Palo Alto, CA, June 1986.
28. P. Tu and D. Padua. Gated SSA-based demand-driven symbolic analysis for parallelizing compilers. In Proc. of the 9th ACM Int. Conf. on Supercomputing, Barcelona, Spain, pp. 414-423, January 1995.
29. M. Wolfe. Beyond induction variables. In ACM SIGPLAN '92 Conf. on Prog. Language Design and Implementation, San Francisco, CA, June 1992.
30. P. Wu, A. Cohen, J. Hoeflinger, and D. Padua. Monotonic evolution: An alternative to induction variable substitution for dependence analysis. In Proc. of the 2001 Int. Conf. on Supercomputing, June 16-21, 2001, Sorrento, Napoli, Italy. ACM, 2001.
31. P. Wu, A. Cohen, and D. Padua. Induction variable analysis without idiom recognition: Beyond monotonicity. In 2007 Workshop on Lang and Compilers for Parallel Computing, number 2624 in LNCS, pp. 427-441, Springer Verlag, Berlin.